Abstract
As a complementary renewable power source, the photovoltaics (PV) has played an increasingly important role in various applications. However, although the PV has been considerably developed in the past decades, the global maximum power point tracking (MPPT) under partial shading conditions still needs to be focused on. In this paper, a novel simulated annealing and particle replacement assisted Gaussian particle swarm optimization algorithm (GPSO) has been proposed. The proposed algorithm has been divided into two stages. In the first stage, the particles are replaced with Gaussian distribution at each iteration to reduce the particle distribution range, and when the distribution range is sufficiently narrow, this stage is completed. In the second stage, the GPSO update was used to track the global maximum power point for the generated particles from the reduced distribution range. The proposed algorithm has been verified with simulation and experiments. Compared with the conventional particle swarm optimization algorithm, the proposed method exhibited considerate improvement for both MPPT time and PV output power stability.
